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Vegetation Biodiversity in Coastal Oregon · PDF file Vegetation Biodiversity in Coastal Oregon • In semi-natural forested landscapes, all ownerships contribute to biodiversity.

May 11, 2020




  • Vegetation Biodiversity in Coastal Oregon Forests

    Janet L. Ohmann and Thomas A. Spies, USDA Forest Service Matthew J. Gregory and K. Norm Johnson, OSU

    • A new kind of vegetation map

    • Uses in CLAMS

    • Current vegetation biodiversity

    Funding by PNW: CLAMS, Northwest Forest Plan, Wood Compatibility Initiative, Forest Inventory and Analysis

  • A Novel Way to Map Vegetation

    Data from plots (FIA, CVS, BLM, OG)

    Climate Geology Topography Ownership

    Remote sensing

    Vegetation maps (1996)

    Spatial data in GIS

    Plot locations

    Statistical model


    41034020 101 TSHE 39.116 24.384 4 83 2.617

    41034020 116 CHLA 109.728 32.309 3 136 2.617

    41034020 123 TSHE 55.880 39.319 3 103 2.617

    41034020 129 PSME 200.152 58.826 3 913 1.000

    41034020 133 PSME 66.802 40.843 3 99 2.617

    41034020 316 TSHE 57.404 40.234 3 80 2.617

    41034020 319 CHLA 105.664 45.110 3 244 2.617

    41034020 320 CHLA 80.518 42.062 4 349 2.617

    A ‘tree list’ for each pixel

  • CLAMS vegetation map ...somewhere SW of Eugene, 1996

  • How good is the CLAMS vegetation map?

    • Assessed accuracy using a variety of methods

    • Excellent representation of regional patterns and variability, landscape proportions

    • Reasonable representation of fine-scale pattern, inexact for specific sites, similar to other satellite-based maps

    • Rare species and habitats not well represented

    • For more information:

    – Posters – Ohmann, J.L.; Gregory, M.J. 2002. Predictive mapping of forest composition

    and structure with direct gradient analysis and nearest neighbor imputation in coastal Oregon, USA. Canadian Journal of Forest Research 32:725-741.

  • Uses of Vegetation Map in CLAMS

    • Initial conditions (1996) for landscape simulations

    • Response models for wildlife, aquatic, timber

    • ‘Big picture’ vegetation conditions

    • Current vegetation biodiversity

    Current policy

    Alt A

    Alt B

    Alt C

    Natural Processes

    Landowner Behavior

    t =1 Biophysical Response t =n

    Landscape/ Watershed Condition

    t =1 t =n

    Socio-economic Response t =1

    Coast Range Ecosystem

    t =n

    CLAMS conceptual model

  • Forest Types and Management Objectives • About 1/3 of each forest type managed for ecological goals


    • Foothill oak woodlands: 94% on private lands, few reserves, threatened by nonforest development.







    Sitka spruce Western hemlock

    P. silver fir/noble fir

    Dry w.hemlock/

    mixed evergreen

    Foothill oak woodlands

    Timber primary

    Timber and other goals

    Ecological primary, timber secondary

    Ecological only

    No-harvest reserves

    Timber goals


    Ecological goals


  • Natural legacies after wildfire

    Lack of legacies under intensive management

    Forest management w/ legacies

    Legacy Trees

  • Key Findings: Vegetation Biodiversity in Coastal Oregon

    • In semi-natural forested landscapes, all ownerships contribute to biodiversity.

    • Some biodiversity elements (tree species, forest types) are relatively insensitive to forest management practices: conservation must consider regional environmental gradients.

    • Forest types represented in reserves EXCEPT foothill oak woodlands.

    • Older forests: small part of current landscape and below HRV, but being addressed by current policies. Diverse young forests: also rare but receiving less attention. Legacy tree habitat: uncertain future.

  • What’s so novel about the CLAMS vegetation map? (i.e., advantages for ecological analysis,

    simulation modeling, integrated assessment)

    • Spatially complete, regional in scope, AND rich in detail (tree species and structures)

    • Each pixel contains a tree list, from which many continuous vegetation variables can be derived. User-defined classification systems can be applied to meet a variety of objectives.

    • At regional level, full range of variability is represented. At site level, covariance of species and structures is maintained.

    • Use of mapped environmental data results in models that better capture ecological relationships.

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